An object model and database for functional genomics

MOTIVATION: Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. RESULTS: We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI-Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. AVAILABILITY: FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.     

An analysis of extensible modelling for functional genomics data

Background  

Several data formats have been developed for large scale biological experiments, using a variety of methodologies. Most data formats contain a mechanism for allowing extensions to encode unanticipated data types. Extensions to data formats are important because the experimental methodologies tend to be fairly diverse and rapidly evolving, which hinders the creation of formats that will be stable over time.     

Non-linear mapping for exploratory data analysis in functional genomics

Background  

Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory, visualisation-driven approaches. Such approaches should satisfy the following factors: Support for intuitive cluster visualisation, user-friendly and robust application, computational efficiency and generation of biologically meaningful outcomes. This research assesses a relaxation method for non-linear mapping that addresses these concerns. Its applications to gene expression and protein-protein interaction data analyses are investigated     

A highly efficient transformation protocol for Micro-Tom, a model cultivar for tomato functional genomics

We report a highly efficient protocol for the Agrobacterium-mediated genetic transformation of a miniature dwarf tomato (Lycopersicon esculentum), Micro-Tom, a model cultivar for tomato functional genomics. Cotyledon explants of tomato inoculated with Agrobacterium tumefaciens (Rhizobium radiobacter) C58C1Rif(R) harboring the binary vector pIG121Hm generated a mass of chimeric non-transgenic and transgenic adventitious buds. Repeated shoot elongation from the mass of adventitious buds on selection media resulted in the production of multiple transgenic plants that originated from independent transformation events. The transformation efficiency exceeded 40% of the explants. This protocol could become a powerful tool for functional genomics in tomato.     

DroPhEA: Drosophila phenotype enrichment analysis for insect functional genomics

SUMMARY: DroPhEA is a core module of a web application that facilitates research in insect functional genomics through enrichment analysis on mutant phenotypes of fruit fly (Drosophila melanogaster). The phenotypes investigated in the analyses can be predefined by FlyBase or customized by users. DroPhEA allows users to specify mutation or ortholog types, displays enriched term results in a hierarchical structure and supports analyses on gene sets of all insect species with a fully sequenced genome.     

A functional genomics approach using metabolomics and in silico pathway analysis

In the field of functional genomics increasing effort is being undertaken to analyze the function of orphan genes using metabolome data. Improved analytical equipment allows screening simultaneously for a high number of metabolites. Such metabolite profiles are analyzed using multivariate data analysis techniques and changes in the genotype will in many cases lead to different metabolite profiles. Here, a theoretical framework that may be applied to identify the function of orphan genes is presented. The approach is based on a combination of metabolome analysis combined with in silico pathway analysis. Pathway analysis may be carried out using convex analysis and a change in the active pathway structure of deletion mutants expressed in a different metabolite profile may disclose the function or the functional class of an orphan gene. The concept is illustrated using a simplified model for growth of Saccharomyces cerevisiae.     

RNAi for plant functional genomics

A major challenge in the post-genome era of plant biology is to determine the functions of all the genes in the plant genome. A straightforward approach to this problem is to reduce or knock out expression of a gene with the hope of seeing a phenotype that is suggestive of its function. Insertional mutagenesis is a useful tool for this type of study, but it is limited by gene redundancy, lethal knock-outs, nontagged mutants and the inability to target the inserted element to a specific gene. RNA interference (RNAi) of plant genes, using constructs encoding self-complementary 'hairpin' RNA, largely overcomes these problems. RNAi has been used very effectively in Caenorhabditis elegans functional genomics, and resources are currently being developed for the application of RNAi to high-throughput plant functional genomics.     

A diploid wheat TILLING resource for wheat functional genomics

Background

Cultivated peanut (Arachis hypogaea L.) is an important crop worldwide, valued for its edible oil and digestible protein. It has a very narrow genetic base that may well derive from a relatively recent single polyploidization event. Accordingly molecular markers have low levels of polymorphism and the number of polymorphic molecular markers available for cultivated peanut is still limiting.

Results

Here, we report a large set of BAC-end sequences (BES), use them for developing SSR (BES-SSR) markers, and apply them in genetic linkage mapping. The majority of BESs had no detectable homology to known genes (49.5%) followed by sequences with similarity to known genes (44.3%), and miscellaneous sequences (6.2%) such as transposable element, retroelement, and organelle sequences. A total of 1,424 SSRs were identified from 36,435 BESs. Among these identified SSRs, dinucleotide (47.4%) and trinucleotide (37.1%) SSRs were predominant. The new set of 1,152 SSRs as well as about 4,000 published or unpublished SSRs were screened against two parents of a mapping population, generating 385 polymorphic loci. A genetic linkage map was constructed, consisting of 318 loci onto 21 linkage groups and covering a total of 1,674.4 cM, with an average distance of 5.3 cM between adjacent loci. Two markers related to resistance gene homologs (RGH) were mapped to two different groups, thus anchoring 1 RGH-BAC contig and 1 singleton.

Conclusions

The SSRs mined from BESs will be of use in further molecular analysis of the peanut genome, providing a novel set of markers, genetically anchoring BAC clones, and incorporating gene sequences into a linkage map. This will aid in the identification of markers linked to genes of interest and map-based cloning.     

嗜热四膜虫——具有发展潜力的功能基因组学研究模型

在真核生物的分子生物学和遗传学研究方面,纤毛类原生动物嗜热四膜虫(Tetrahymenathermophila)已经被证明是一种有价值的生物学模型。通过对它的研究,人们发现并且掌握了核酶的分子机制、RNA的自我拼接、端粒的结构和功能、DNA序列重组等机理。这种原生动物的基因组功能分别由两个细胞核执行,即二倍体的小核与生殖过程有关,而多倍体的大核决定细胞的基因转录,并为转化基因的表达提供了强有力的手段。     

DNA microarrays for functional plant genomics

DNA microarray technology is a key element in today's functional genomics toolbox. The power of the method lies in miniaturization, automation and parallelism permitting large-scale and genome-wide acquisition of quantitative biological information from multiple samples. DNA microarrays are currently fabricated and assayed by two main approaches involving either in situ synthesis of oligonucleotides (`oligonucleotide microarrays') or deposition of pre-synthesized DNA fragments (`cDNA microarrays') on solid surfaces. To date, the main applications of microarrays are in comprehensive, simultaneous gene expression monitoring and in DNA variation analyses for the identification and genotyping of mutations and polymorphisms. Already at a relatively early stage of its application in plant science, microarrays are being utilized to examine a range of biological issues including the circadian clock, plant defence, environmental stress responses, fruit ripening, phytochrome A signalling, seed development and nitrate assimilation. Novel insights are obtained into the molecular mechanisms co-ordinating metabolic pathways, regulatory and signalling networks. Exciting new information will be gained in the years to come not only from genome-wide expression analyses on a few model plant species, but also from extensive studies of less thoroughly studied species on a more limited scale. The value of microarray technology to our understanding of living processes will depend both on the amount of data to be generated and on its clever exploration and integration with other biological knowledge arising from complementary functional genomics tools for `profiling' the genome, proteome, metabolome and phenome.